The Humber Opportunity: AI for Net Zero, Net Zero for AI: An Employee Perspective

Recently, I had the opportunity to attend The Humber Opportunity: AI for Net Zero, Net Zero for AI, an event that brought together industry experts, academics, and practitioners to explore the relationship between artificial intelligence (AI) and sustainability.

With a background spanning renewable energy, AI, and digital marketing, this felt particularly relevant to me, not just professionally, but in how I think about applying these technologies in the real world. It was not just about what AI can do, but what it should do, and also what it should not.

AI as a Tool, Not a Strategy

One of the main takeaways was a simple idea that some businesses still struggle with: AI is not a strategy, it is a tool.

There is often an eagerness to add AI into campaigns and workflows without a clear problem being solved. This can create more complexity rather than better performance.

The value of AI comes from applying the right model to the right task. In some of the work we do, we see that you do not always need a complex model to drive impact. A structured approach that combines rules, classification, and a targeted AI layer can group queries, highlight opportunities, and support decisions at scale.

You also do not always need to build from scratch. Transfer learning, where pre-trained models are adapted to specific tasks, can deliver strong results with far less computational cost. This is more efficient and better aligned with net zero thinking.

In many cases, using the biggest model is not the best option. If a system can flag wasted spend or automate routine actions effectively, then it is already doing its job. Using a large model where it is not needed does not point to innovation, it points to inefficiency.

Sustainability: Beyond the Environment

Sustainability was a key theme, but one point stood out. It is not just environmental, it is also economic.

Large AI models do have a carbon footprint, but there is also a business reality. If a solution does not deliver measurable value, then it is not sustainable.

In practical terms, that means asking simple questions:

• Does it reduce wasted spend?
• Does it improve efficiency?
• Does it support better decisions?

If not, then the technology itself becomes less important.

The Role of Human Intelligence

Despite everything AI can do, predicting human behaviour is still difficult. Two people can see the same message and respond very differently, and performance can change quickly.

This is why human input still matters. AI is good at identifying patterns and working at scale, but context and judgement sit with people.

The strongest outcomes come from combining both:

AI to surface insights and handle scale

Human to decide what actually matters.

Embedding AI

Another point that stood out was the need to embed AI into workflows rather than adding more reporting.

Most organisations already have a lot of data. More dashboards do not always lead to better decisions.

The real impact comes when AI is used to:

• flag issues,
• prioritise actions, and
• support decisions in real time.

Moving from reporting what happened to suggesting what to do next is where the value sits.

Final Thoughts

The key takeaway is quite simple:

Success will not come from using the most complex models, but from using the most appropriate ones.

That is where real impact sits.

At Summit, this is something we are actively working on across data, media, and technology. If you are thinking about how to apply AI in a way that is practical, measurable, and aligned with your business goals, get in touch with our team, it is a conversation worth having.

By Williams Ossai, Data and Analytics Specialist, Summit Media Ltd